. Author manuscript; available in PMC: 2019 Aug 29.

Published in final edited form as: Expert Syst Appl. 2016 Jan 25;54:136–147. doi: 10.1016/j.eswa.2016.01.029

Table 4.

Summary of performance for HF ScoreCard versus BNP. Sensitivity, specificity, PPV, and NPV (95% confidence intervals) are determined by optimal cutoff given by ROC analysis.

	BNP	HF ScoreCard
AUC	0.9320 (0.8936 – 0.9704)	0.9412 (0.9053 – 0.9771)
Sensitivity	0.8313 (0.7871 – 0.8684)	0.8554 (0.8133 – 0.8899)
Specificity	0.8959 (0.8580 – 0.9252)	0.9145 (0.8790 – 0.9410)
PPV	0.7113 (0.6604 – 0.7577)	0.7553 (0.7063 – 0.7988)
NPV	0.9451 (0.9145 – 0.9661)	0.9535 (0.9245 – 0.9727)
Training error	-	0.1614
Test error	-	0.1810